Association of osteoporosis with sarcopenia and its components among community-dwelling older Chinese adults with different obesity levels: A cross-sectional study

We aimed to investigate whether sarcopenia and its components are associated with osteoporosis in community-dwelling older Chinese adults with different obesity levels. This cross-sectional study included 1938 participants (42.1% male) with a mean age of 72.1 ± 5.9 years. The categorization of individuals into various weight categories was based on the Working Group on Obesity in China’s criteria, utilizing the body mass index (BMI) as follows: underweight, BMI < 18.5 kg/m2; normal weight, 18.5 ≤ BMI < 24 kg/m2; overweight, 24 ≤ BMI < 28 kg/m2; and obesity, BMI ≥ 28 kg/m2. In this research, the osteoporosis definition put forth by the World Health Organization (bone mineral density T-score less than or equal to −2.5 as assessed by Dual-energy X-ray absorptiometry (DXA)). Sarcopenia was defined according to the diagnostic criteria of the Asian Working Group for Sarcopenia. The prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI (Underweight: 55.81% vs Normal weight: 45.33% vs Overweight: 33.69% vs Obesity: 22.39). Sarcopenia was associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates (OR = 1.70, 95% CI = 1.22–2.35, P = .002). In normal-weight participants, a higher appendicular skeletal muscle mass index (ASMI) was associated with a reduced risk of osteoporosis (OR = 0.56, 95% CI = 0.42–0.74, P < .001). In this study, we found that the prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI. Sarcopenia, body fat percentage, and ASMI were associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates, and higher percent body fat (PBF) was associated with an increased risk of osteoporosis in overweight people, and no such association was found in other weight groups. Different amounts of adipose tissue and muscle mass may alter bone biology. Further longitudinal follow-up studies are required to more accurately assess the risk of osteoporosis and sarcopenia in different weight populations. This cross-sectional study found that the prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI. Sarcopenia was associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates.


Introduction
Osteoporosis, defined as decreased bone quantity and quality, is a major public health concern.Worldwide, one in 2 women aged ≥ 50 years and one in 5 men aged ≥ 50 years will have an osteoporotic fracture in their lifetime. [1]Aging-related hormonal changes, along with decreased physical activity, promote bone resorption and inhibit bone formation.In the elderly population, the risk of fractures is exacerbated by muscle wasting and sarcopenia. [2,3]he World Health Organization defines obesity as the accumulation of excessive fat, which is a growing societal issue with potential health implications. [4]Several studies have suggested that higher body weight may attenuate bone loss during menopause, and the mechanical impact of increased body weight on bones may contribute to the positive effects of obesity on bone mineral density (BMD). [5,6]Garnero et al discovered a reduction in biochemical bone markers among obese individuals, notably a more significant drop in bone resorption markers compared to bone formation markers.Obese people exhibit an increase in both fat mass and lean mass, yet it is the latter that positively contributes to bone density, as evidenced by Gkastaris' findings. [7,8]The influence of mechanical loading on bone is predominantly determined by lean mass, rather than fat mass. [9,10]owever, some researchers have observed an augmentation in bone mass at the lumbar spine, radius, and tibia in obese women, but not in men. [11]While estrogens produced by adipose tissue positively influence bone metabolism by enhancing bone formation and diminishing bone resorption, obesity has been linked to a heightened risk of various diseases and chronic inflammation. [12][15] The impact of obesity, as determined by the body mass index (BMI), on bones remains a topic of debate.
The occurrence of osteoporosis is influenced by various physiological mechanisms that underlie sarcopenia and obesity, encompassing alterations in body composition, shifts in muscle fiber types, hormonal level reductions, inflammation, psychosocial factors, the development of joint pain, and a sedentary lifestyle. [16]A strong correlation between osteoporosis and sarcopenia has been suggested by numerous pieces of evidence, stemming from observational studies.. [17,18] Some studies suggest a bidirectional association between osteoporosis and sarcopenia. [18,19]However, there are still different conclusions regarding components related to sarcopenia, such as muscle strength and physical function, especially in populations with different obesity levels. [4,20,21]For a long time, it was believed that the agerelated decrease in weight, along with the loss of muscle mass, was primarily accountable for muscle weakness and sarcopenia among older people. [22]However, with aging, physical activity decreases, which may lead to weight gain, primarily with an increase in visceral abdominal fat, which leads to sarcopenic obesity. [23]Thus, in this study, we aimed to investigate whether sarcopenia and its components were associated with osteoporosis among community-dwelling older Chinese adults with different obesity levels.

Study participants
This cross-sectional study enrolled patients participating in the Adult Physical Fitness and Health Cohort Study (APFHCS) [ChiCTR1900024880].The APFHCS, a significant prospective dynamic cohort research, primarily delved into the correlation between physical fitness and health conditions in China's general adult populace.Our study encompassed 2169 senior citizens (aged 60 and above) hailing from Shanghai, China.Each participant underwent an annual health examination and a thorough questionnaire focusing on their lifestyle habits and medical histories.This endeavor adhered to the recommendations of both national and international guidelines, as well as the standards set by our ethical committee.
All participants provided written informed consent by the Declaration of Helsinki.The study protocol was approved by the Ethical Committee of the Shanghai University of Medicine and Health Sciences.The inclusion criteria for participants were age ≥ 60 years and completion of the relevant tests.Exclusion criteria were as follows: those unable to provide signed informed consent; those suffering from severe cognitive impairment, dementia, psychiatric disorders, or other neurodegenerative diseases; those with severe visual and hearing impairments that hindered communication; those unable to stand for the measurement of body composition, weight, and height due to injury, rendering bone density testing unfeasible; and patients who were taking medications that could potentially interfere with bone or calcium metabolism, such as estrogen, calcitonin, and diphosphonate.
A total of 2169 participants participated in the study.

Assessment of BMD
Portable dual-energy X-ray absorptiometry (EXA-3000; OsteoSys, Co., Ltd., 901-914, 9F, Jnk Digitaltower, 111 Digital-ro 26, Guro-gu, Seoul 152-848, Republic of Korea) was used to measure BMD.The area of BMD (g/cm 2 ) was measured at the distal one-third radius of the non-stressed forearm.The daily calibration of the densitometers was carried out by trained technicians using equipment-specific phantoms, and they also conducted all examinations.The World Health Organization's definition of osteoporosis (BMD T-score less than or equal to −2.5 as assessed by dual-energy X-ray absorptiometry) was adopted for this research. [24]

Assessment of obesity
Body composition analysis was performed using direct segmental multi-frequency bioelectrical impedance analysis (BIA) (In-Body720; Biospace Co, Ltd, Seoul, Korea).One hour prior to the assessment, participants were instructed to refrain from eating and consuming excessive amounts of water.BIA furnished definitive measurements for appendicular skeletal muscle mass, fat-free mass, PBF, and total body water.The categorization of individuals into various weight categories was based on the Working Group on Obesity in China's criteria, utilizing the BMI as follows: underweight, BMI < 18.5 kg/m 2 ; normal weight, 18.5 ≤ BMI < 24 kg/m 2 ; overweight, 24 ≤ BMI < 28 kg/m 2 ; and obesity, BMI ≥ 28 kg/m 2 . [25]

Assessment of sarcopenia
The definition of sarcopenia was formulated in accordance with the diagnostic standards established by the Asian Working Group for Sarcopenia (AWGS), encompassing both low muscle mass, as well as low muscle strength and/or poor physical performance, details of measurement methods can be found in our previous study. [24]Muscle mass was measured using direct segmental multifrequency BIA (In-Body720; Biospace Co., Ltd.).Low muscle mass was diagnosed as a skeletal muscle index (ASM/ht 2 ) lower than 7.0 and 5.7 kg/m 2 in men and women, respectively.Muscle strength was evaluated by grip strength using a dynamometer (GRIP-D; Takei Ltd., Niigata, Japan).Participants were asked to exert maximum effort twice using their dominant hand, and the www.md-journal.comresult from the strongest hand was used for the analysis.Low muscle strength was defined as grip strength < 26 and < 18 kg in males and females, respectively.Usual gait speed was used as an objective measurement of physical performance, poor physical performance was assessed by gait speed which was less than 0.8 m/s in both men and women.

Covariates
The standardized questionnaire was administered to all invited participants during a face-to-face interview, aiming to gather data on sociodemographic profiles, health-related habits, and the status of chronic diseases.These factors served as covariates, as outlined in our previous research. [24]Among the sociodemographic factors, we collected information on gender, age, educational attainment, monthly earnings, living arrangements, and marital status.Additionally, the participants' physical activity levels and sitting durations in the past week were evaluated utilizing the concise version of the International Physical Activity Questionnaire. [26]The assessment of grip strength (in kilograms) was carried out with the aid of a handheld dynamometer (GRIP-D, Takei Ltd).Furthermore, to assess walking speed, 2 sets of laser-based timing devices were positioned at the start and finish of a 4-meter course.The participants were instructed to traverse the 4-meter distance at their regular, steady pace.The medical history was taken to record whether the participants had diabetes mellitus (T2DM), hypertension, hyperlipidemia, cardiovascular disease, pulmonary disease, stroke, etc.

Statistical analysis
The sociodemographic, lifestyle, and health-related characteristics of participants were presented according to the categories of osteoporosis prevalence based on the categorized BMI.When evaluating the disparities in baseline traits, continuous data points were portrayed by their average ± the standard deviation, employing either the t test or the Mann-Whitney U tests.Meanwhile, categorical variables were expressed as percentages, analyzed through the chi-square test.Logistic regression analysis was used to analyze the relationship between PBF, sarcopenia, appendicular skeletal muscle mass index (ASMI), grip strength, walking speed, and osteoporosis in the study population categorized by BMI.The results are expressed as odds ratios (OR), 95% confidence intervals (CIs), and corresponding P value.The confounding factors of sex, age, smoking and drinking habits, living conditions, and history of diseases were adjusted.Statistical significance was set at P < .05.SPSS v26.0 (https:// www.ibm.com/cn-zh/products/spss-statistics?lang=en_US) was used the statistical analysis.

Results
The final study included 1938 participants (42.1% male) with a mean age of 72.1 ± 5.9 years.The prevalence of osteoporosis was 39.47% in all participants.Overall, 4.4% of the subjects were underweight, 51.3% had normal weight, 33.8% were overweight, and 10.4% were obese.The prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI, as shown in Figure 1.
The overall characteristics of the study population and according to categories of prevalence of osteoporosis based on BMI are shown in Table 1.In the underweight group, people with lower activity levels and shorter sleep durations were more likely to suffer from osteoporosis (P < .05).People with significantly lower muscle mass and higher body fat percentage were more likely to have osteoporosis in the normal-weight and overweight groups and had lower activity levels (P < .05).In the obesity group, people with significantly lower walking speed and older age were more likely to develop osteoporosis (P < .05).The prevalence of osteoporosis was higher in female subjects in the normal-weight and overweight groups (P < .05),as shown in Table 1.
Results of the logistic regression analyses for osteoporosis with sarcopenia and its components in underweight subjects are shown in Table 2.After adjusting for potential confounders (sex, age, smoking, drinking habits, living conditions, and history of diseases), we did not observe significant differences in underweight subjects with and without osteoporosis.
The results of the logistic regression analyses for osteoporosis with sarcopenia and its components in overweight and obese subjects are shown in Tables 4 and 5.After adjusting for potential confounders, we observed that PBF (OR = 1.09, 95% CI = 1.04-1.14)was significantly correlated with osteoporosis in overweight subjects.

Discussion
In this study, we found that the prevalence of osteoporosis was highest in the underweight group and gradually decreased with an increase in BMI, and higher PBF was significantly correlated with an increased risk of osteoporosis in normal weight and overweight subjects.Sarcopenia was associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates.In normal-weight participants, a higher ASMI was associated with a reduced risk of osteoporosis.

Weight and osteoporosis
Several studies have shown a positive relationship between BMI and BMD, which is similar to our findings. [4,27]Previous studies have reported that higher body weight appears to decelerate bone loss during menopause, and the beneficial effects of obesity on BMD can be attributed to the mechanical impact of body weight on bones. [5,6]Animal-based investigations reveal that osteocytes possess a heightened sensitivity to biomechanical stress.Upon detection of shear stress signals by osteocytes, the release of sclerostin is inhibited, the activity of osteoclasts is diminished, and the differentiation of osteoblasts is stimulated.This substantiates the notion that an increase in body weight contributes to a favorable bone balance. [4,28]In a comparable fashion, research encompassing 1988 young Chinese individuals and 4489 elderly Caucasians demonstrated a reverse association between body fat percentage and weight-adjusted bone mass, taking into account variables such as age, gender, height, menopausal status, and lifestyle factors, [29] additionally, a study involving 1147 patients over 18 years of age revealed a negative correlation between body fat percentage and BMD, with adjustments for age, weight, height, ethnicity, and menopausal status. [30]Therefore, not only passive loading but also muscleinduced strain is increased to decrease the risk of osteoporosis. [31]n contrast, obesity, manifesting as a low-grade chronic inflammatory state, triggers the release of numerous cytokines detrimental to bone and muscle health, resulting in fatty infiltration of muscles and subsequently diminishing their strength and efficiency. [32]Furthermore, obese individuals exhibit elevated levels of body fat and lean tissue mass, which have been linked to heightened circulating concentrations of proinflammatory cytokines.These cytokines have been associated with reduced BMD, accelerated bone deterioration, and an elevated risk of fractures among older adults. [33]In our study, we found that higher PBF was significantly correlated with an increased risk of osteoporosis in normal-weight and overweight subjects, which is consistent with some previous studies. [30,34]n this study, we found that the prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI.The seeming obscurity surrounding the higher values in terms of BMD could be partially attributed to the well-established connection between estrogens and obesity.Studies reveal that obese postmenopausal women possess higher blood estrogen concentrations compared to their nonobese counterparts, [29,35] which might elucidate the correlation between greater BMD and higher BMI among females.Nevertheless, estrogen levels alone do not solely govern bone   mass, as numerous other factors also influence both bone and fat mass.High body fat is associated with inflammation and various adverse health outcomes, encompassing elevated mortality and metabolic disorders like diabetes and osteoporosis. [20,36]Among the elderly, the relatively elevated visceral fat might have escalated the risk of osteoporosis, according to the body fat percentage.Individuals with high visceral fat exhibit a negative correlation with BMD due to augmented bone resorption triggered by proinflammatory cytokines and reduced bone formation stemming from insulin resistance and low insulin-like growth factor levels. [37]Given the advantageous impact of bodily weight's mechanical influence on bones, particularly from lean mass, the introduction of mechanical stimuli through exercise fosters pathways that aid in bone maintenance and growth. [2]

Sarcopenia and osteoporosis
Sarcopenia and osteoporosis, being 2 prevalent age-related disorders, frequently occur concurrently.Amidst the aging    demographic, it is anticipated that the incidence of both these conditions will escalate in the forthcoming years, thereby heightening the vulnerability to fragility fractures, which are closely linked to considerable morbidity and mortality. [38]In this study, we found that sarcopenia was associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates.We did not find any coexistence of osteoporosis and sarcopenia in obese individuals as defined by BMI classification.
Other methods of defining obesity may need to be introduced to more accurately assess the risk of osteoporosis and sarcopenia in different populations.Epidemiological investigations have revealed a positive correlation between osteoporosis, sarcopenia, and C-reactive protein (CRP), a biomarker indicating active inflammation. [39]A systematic review and meta-analysis has underscored the significant prevalence of osteosarcopenia across various geriatric populations, regardless of the varying definitions of sarcopenia.Muscle tissue is widely acknowledged as the primary generator of anabolic mechanical stimuli for bone, and a reduction in mechanical loading contributes to diminished bone formation, ultimately resulting in fragile bone status. [19]umerous studies have indicated a connection between handgrip strength and a spectrum of health outcomes.Notably, a diminished level of handgrip strength is associated with a higher likelihood of multimorbidity in older adults, even after considering adjustments. [40,41]Our study did not find a significant correlation between muscle function and osteoporosis, which may be due to the differences in muscle function assessment methods by sarcopenia.Our previous research has shown that when dynamic balance ability is used as a supplement to sarcopenia's muscle function assessment, it has higher predictive value for osteoporosis. [24]In a study conducted in vitro, researchers analyzed osteoblasts cultured with serum from participants categorized as normal, obese, obese/osteopenic, obese/sarcopenic, and obese/osteopenic/sarcopenic.Their findings revealed a diminished level of RunX2, a crucial transcription factor for osteoblast maturation, in all pathological groups when compared to healthy controls.However, notable changes in the osteoblast marker osteocalcin were observed only in obese participants, not in those with a combined obese, osteopenic, and sarcopenic status.This suggests that varying degrees of adipose tissue and muscle mass may influence bone biology. [42]s this was a cross-sectional study, causality could not be evaluated.The participants of the current study were predominantly in a good health state, excluding those who were unable to engage in the annual national physical examination due to limitations (such as bedridden individuals or those with critical illnesses).Consequently, there is a likelihood that our findings underestimated the prevalence of osteoporosis and its related health consequences.Nevertheless, noteworthy disparities between participants with and without osteoporosis remained evident, indicating that statistical power was unlikely to be a significant concern.Further longitudinal follow-up studies are required.

Conclusions
In this study, we found that the prevalence of osteoporosis was highest in the underweight group and gradually decreased with increasing BMI.Sarcopenia, PBF, and ASMI were associated with elevated odds of osteoporosis in normal-weight subjects independent of potential covariates, and a higher PBF was associated with an increased risk of osteoporosis in overweight people, no such association was found in other weight groups.Different amounts of adipose tissue and muscle mass may alter bone biology.Further longitudinal follow-up studies are required.

Figure 1 .
Figure 1.Prevalence (%) of osteoporosis based on the categorized of BMI among the study population.

Table 1
Characteristics of the study population overall and according to categories of prevalence of osteoporosis based on the categorized of BMI.

Table 2
Logistic regression analyses for osteoporosis with sarcopenia and its components in underweight subjects.adjusted for gender and age.Model 2 was adjusted for Model 1 variables, in addition to smoking and drinking habits, living conditions, physical activity, marital status and history of diseases.BFM = body fat mass, PBF = percent body fat, SMI = skeletal muscle index, SMM = skeletal muscle mass, WS = walking speed.

Table 3
Logistic regression analyses for osteoporosis with sarcopenia and its components in normal weight subjects.Model 1 was adjusted for gender and age.Model 2 was adjusted for Model 1 variables, in addition to smoking and drinking habits, living conditions, physical activity, marital status and history of diseases.BFM = body fat mass, PBF = percent body fat, SMI = skeletal muscle index, SMM = skeletal muscle mass, WS = walking speed.

Table 4
Logistic regression analyses for osteoporosis with sarcopenia and its components among overweight subjects.
Model 1 was adjusted for gender and age.Model 2 was adjusted for Model 1 variables, in addition to smoking and drinking habits, living conditions, physical activity, marital status and history of diseases.BFM = body fat mass, PBF = percent body fat, SMI = skeletal muscle index, SMM = skeletal muscle mass, WS = walking speed.

Table 5
Logistic regression analyses for osteoporosis with sarcopenia and its components among obesity subjects.